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Assembly activities can be complex tasks that have manual operation processes. They develop and require a lot of expertise at the individual level. This accumulated expertise is knowledge that any company needs to convert from an individual to an organizational level. A company that loses its knowledge has little chance to register for performance and sustainability (Bibi et al., 2020; Zaim et al., 2019). The process that allows this conversion is called OKM.
Krafcik (1988) analyzed performance indicators at world auto assembly plants and admitted that an “experienced, well-trained, and well-educated workforce can be expected to perform at a higher level of efficiency” (Krafcik, 1988). Piotr Tworek (2011) conducted a study to analyze risk factors in the activities of large construction and assembly companies (Tworek, 2011). The study ranks employees’ qualifications and experience in the eight main risk factors that construction and assembly companies may consider to master their activities. An analysis of the automation assembly industry in Japan stated that adapting to an aging workforce is the fifth objective of assembly automation (Fujimoto, 1992). Assembly companies have difficulties replacing senior, experimented workers. This may reveal that there is a difficulty in ensuring knowledge capture and transfer.
The OKM is not an easy task in the assembly field regarding the form of the knowledge concerned. While several studies confirm the close relationship between knowledge management, performance, and sustainability of companies (Nguyen & Prentice, 2020; López-Cabarcos et al., 2019; López-Torres et al., 2019; Rasula et al., 2012; Zack et al., 2009; Aaron, 2009; Darroch, 2005), others reveal the complexity of this process in the assembly field (Gavish et al., 2011; Gutierrez et al., 2010).
An interesting study states that industrial maintenance and assembly tasks “involve the knowledge of specific procedures and techniques for each machine” (Gutierrez et al., 2010). These techniques require cognitive memory and expertise to master “precise movements and forces” (Gutierrez et al., 2010). This technical description matches the definition that Nonaka and Takeuchi gave to tacit knowledge (Nonaka & Takeuchi, 1995).
Indeed, there are two forms of knowledge; tacit knowledge that refers to knowledge that resides in the human mind, behavior, experience, expertise, and perception; and explicit knowledge that can be readily articulated, codified, stored, and accessed on manuals, documents, procedures, videos, etc. (Nonaka & Takeuchi, 1995). The knowledge management approach can only be effective if it takes into account both forms of knowledge (Goh, 2002).
Tacit knowledge is the most difficult to manage in all sectors (Muthuveloo et al., 2017; Gubbins et al., 2012; Argote & Ingram, 2000; Nonaka & Toyama, 2015) and particularly in the assembly sector. The biggest challenge concerning this form of knowledge is the capture and sharing of knowledge (Agrawal & Mukti, 2020; Grant, 1996). While, this form of knowledge needs to be formalized and converted into words, numbers, or pictures that can be understood by others (Iqbal, 2017); it can be difficult in manual assembly to express, for example, the experience, manual dexterity, and cutting precision. Importing the tacitness of manual tasks to an organization is a real competitive advantage (Grant, 1996). Performance of assembly companies strongly depends on the organizational knowledge they develop (Gutierrez et al., 2010). The relationship between KM especially tacit KM and performance is no longer to be proven (Muthuveloo et al., 2017; Sousa, 2017).